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Inverse Solutions of Convective Heat Transfer Problems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Inverse Solutions of Convective Heat Transfer Problems./
作者:	Bangian Tabrizi, Ardeshir.
面頁冊數:	1 online resource (99 pages)
附註:	Source: Dissertations Abstracts International, Volume: 82-01, Section: B.
Contained By:	Dissertations Abstracts International82-01B.
標題:	Mechanical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27738092click for full text (PQDT)
ISBN:	9798662404724

Inverse Solutions of Convective Heat Transfer Problems.
Bangian Tabrizi, Ardeshir.

Inverse Solutions of Convective Heat Transfer Problems. - 1 online resource (99 pages)

Source: Dissertations Abstracts International, Volume: 82-01, Section: B.

Thesis (Ph.D.)--Rutgers The State University of New Jersey, School of Graduate Studies, 2020.

Includes bibliographical references

Inverse problems are well known in nearly every discipline of science and engineering. In mechanical engineering, in particular, inverse heat transfer problems have always been a major focus for research and improvement. Inverse heat transfer solutions are usually needed when direct measurement of a boundary condition, commonly in the form of temperature, or a thermophysical property of a material, is not feasible. Estimating the aerodynamic heating on a reentering shuttle heat shields or approximating the temperature dependence of thermal conductivity of a cooled ingot during steel tempering are examples of inverse heat transfer applications in engineering.A new inverse methodology to tackle the inverse heat convection problem of a wall plume is studied and presented here. A detailed study of the forward problem is developed, and the results are used to build the inverse solution methodology. Through studying the forward problem, unique interpolating functions relating plume heat source strength and location to various flow features such as steady-state temperature on the wall downstream of the plume, are developed. These functions would form up a system of equations through which plume source strength and location are estimated. A search-based optimization method, particle swarm optimization (PSO), is used to minimize the estimation error through improving the system of equations. In the first study, numerically simulated steady-state laminar and turbulent wall plume flows are considered. Temperature variations on the wall prove to have a unique correlation with the heat input and location of the plume. Our proposed method formulates these relations into mathematical functions for distinct locations on the wall, downstream of the plume. PSO would choose the best pair, or more, of locations on the wall to read the temperatures and form up a system of equations to solve for plume heat source strength and location. Results demonstrate high accuracy in estimating both unknowns.The second study focuses on the transient behavior of the laminar wall plume flow. It is shown that the time it takes for the temperature, at any given location downstream of the flow, to reach a maximum across the boundary layer is related to plume heat input and location. The methodology formulates these functions and PSO would find the optimal data points on the wall to form up the system of equations. The results of this study also demonstrate high accuracy in estimating both plume strength and location.The third study is about testing the methodology against experimental data. An experiment setup of the wall plume problem was built and temperatures on the wall downstream of the plume were measured. To test the robustness of the methodology, the same relative functions derived in the first study are applied to the experimental data to great success. The inverse solution produces accurate estimations of the heat input and source location with the experiment data as well.The ultimate goal of this project is to provide an inverse solution to rapidly and accurately respond in applications that include free convection heat transfer, such as overheating of electronic devices and small fires in data centers and small rooms. To that end, the proposed methodology could be considered as the first step towards a more complex and general inverse heat convection solution.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798662404724Subjects--Topical Terms:

649730
Mechanical engineering.
Subjects--Index Terms:

CFDIndex Terms--Genre/Form:

542853
Electronic books.

Inverse Solutions of Convective Heat Transfer Problems.
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500 $a Source: Dissertations Abstracts International, Volume: 82-01, Section: B.
500 $a Advisor: Jaluria, Yogesh.
502 $a Thesis (Ph.D.)--Rutgers The State University of New Jersey, School of Graduate Studies, 2020.
504 $a Includes bibliographical references
520 $a Inverse problems are well known in nearly every discipline of science and engineering. In mechanical engineering, in particular, inverse heat transfer problems have always been a major focus for research and improvement. Inverse heat transfer solutions are usually needed when direct measurement of a boundary condition, commonly in the form of temperature, or a thermophysical property of a material, is not feasible. Estimating the aerodynamic heating on a reentering shuttle heat shields or approximating the temperature dependence of thermal conductivity of a cooled ingot during steel tempering are examples of inverse heat transfer applications in engineering.A new inverse methodology to tackle the inverse heat convection problem of a wall plume is studied and presented here. A detailed study of the forward problem is developed, and the results are used to build the inverse solution methodology. Through studying the forward problem, unique interpolating functions relating plume heat source strength and location to various flow features such as steady-state temperature on the wall downstream of the plume, are developed. These functions would form up a system of equations through which plume source strength and location are estimated. A search-based optimization method, particle swarm optimization (PSO), is used to minimize the estimation error through improving the system of equations. In the first study, numerically simulated steady-state laminar and turbulent wall plume flows are considered. Temperature variations on the wall prove to have a unique correlation with the heat input and location of the plume. Our proposed method formulates these relations into mathematical functions for distinct locations on the wall, downstream of the plume. PSO would choose the best pair, or more, of locations on the wall to read the temperatures and form up a system of equations to solve for plume heat source strength and location. Results demonstrate high accuracy in estimating both unknowns.The second study focuses on the transient behavior of the laminar wall plume flow. It is shown that the time it takes for the temperature, at any given location downstream of the flow, to reach a maximum across the boundary layer is related to plume heat input and location. The methodology formulates these functions and PSO would find the optimal data points on the wall to form up the system of equations. The results of this study also demonstrate high accuracy in estimating both plume strength and location.The third study is about testing the methodology against experimental data. An experiment setup of the wall plume problem was built and temperatures on the wall downstream of the plume were measured. To test the robustness of the methodology, the same relative functions derived in the first study are applied to the experimental data to great success. The inverse solution produces accurate estimations of the heat input and source location with the experiment data as well.The ultimate goal of this project is to provide an inverse solution to rapidly and accurately respond in applications that include free convection heat transfer, such as overheating of electronic devices and small fires in data centers and small rooms. To that end, the proposed methodology could be considered as the first step towards a more complex and general inverse heat convection solution.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 649730
650 4 $a Fluid mechanics. $3 528155
653 $a CFD
653 $a Inverse heat transfer
653 $a Optimization
653 $a Wall plume
653 $a Turbulent wall plume flows
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690 $a 0204
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Rutgers The State University of New Jersey, School of Graduate Studies. $b Mechanical and Aerospace Engineering. $3 3435840
773 0 $t Dissertations Abstracts International $g 82-01B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27738092 $z click for full text (PQDT)